fairseq swMATH ID: 30760 Software Authors: Myle Ott; Sergey Edunov; Alexei Baevski; Angela Fan; Sam Gross; Nathan Ng; David Grangier; Michael Auli Description: fairseq: Facebook AI Research Sequence-to-Sequence Toolkit written in Python. Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. Homepage: https://arxiv.org/abs/1904.01038 Source Code: https://github.com/pytorch/fairseq Dependencies: Python; PyTorch Related Software: PyTorch; BERT; Python; AllenNLP; Tensor2Tensor; Transformers; wav2vec; LibriSpeech; TensorFlow; Adam; RoBERTa; Scikit; OpenNMT; Espresso; PyTorch-Kaldi; SentencePiece; PyTorch Lightning; QuartzNet; Jasper; SUPERB Cited in: 4 Documents all top 5 Cited by 18 Authors 1 Bakhtin, Anton 1 Bansal, Yamini 1 Barak, Boaz 1 Camacho-Collados, José 1 Deng, Yuntian 1 Gross, Sam 1 Jorge, Alípio Mário 1 Kaplun, Gal 1 Kool, Wouter 1 Loureiro, Daniel 1 Nakkiran, Preetum 1 Ott, Myle 1 Ranzato, Marc’Aurelio 1 Sutskever, Ilya 1 Szlam, Arthur D. 1 van Hoof, Herke 1 Welling, Max 1 Yang, Tristan Cited in 3 Serials 2 Journal of Machine Learning Research (JMLR) 1 Artificial Intelligence 1 Journal of Statistical Mechanics: Theory and Experiment Cited in 4 Fields 3 Computer science (68-XX) 1 Statistics (62-XX) 1 Statistical mechanics, structure of matter (82-XX) 1 Operations research, mathematical programming (90-XX) Citations by Year